Est-ce que quelqu'un sait comment produire une expression de prédiction en utilisant des termes quadratiques.
Je veux sortir une expression ressemblant à : y = A + Bx + Cx2 - Dx3 au lieu de y = A + Bx + (x-0,5) * [(x-0,5)*C] * ...
Veuillez consulter le aider pour cette fonction. Le premier argument est la matrice de covariance S . Le deuxième argument, formé par concaténation de colonnes, est la matrice du modèle X .
J'ai obtenu un formulaire pour la limite de confiance moyenne d'un modèle d'ajustement. L'expression est extrêmement large comme ci-dessous,
1.96625963553186 * Sqrt(
Vec Quadratic(
[0.0287292895751759 -0.00666060427133376 -0.00420705348654747
-0.000101067994317605 -0.0151558320176791 -0.018006675429998
-0.0105828228409277 0.0525931189072001 -0.00307760776478522
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-0.00358411899712196,
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0.00158305896356562 0.00423442416487127 -0.00049477545256354
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0.00130152304853031 -0.00127260662386009 -0.00011528684291611
0.000314668319013466 0.00263734766595279 -0.00178122861070318
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0.00914757285926523,
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0.00262807321722145 0.0026654907331227 -0.000953584762348311
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0.000907927201776815 -0.00131435643870052 -0.000590273074347901
0.00357311675973109 -0.00335203317054354 -0.00114710879851391
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0.00197347468700018,
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0.0164764002633817 0.00246065900285425 -0.00149703170638324
-0.00328183774362992 0.000649182560833079 0.00127619111302658
-0.00468114540689985 0.000997520645385026 -0.0019928296860267
0.00161500892161912 0.000649182560833082 -0.00264578880577995
0.00106718826229541 0.0042120105942121 0.000510838716778689
0.00266534906695824,
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0.00246065900285425 0.117647453338642 0.0100446758767068 0.0023045234028937
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0.00834904973644429 -0.000472225416095427 -0.000670698384850352,
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0.00953084423684981 -0.0532302927543955 0.00363727880259079
0.00403818130411868 0.00614058033281912 0.0181055932574402
0.00759246318330849 -0.0532302927543955 0.012027509206273
0.00372904066454776 0.011643459524991 0.000395857625121327
-0.00115783914329167,
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-0.00131240178043079,
0.0525931189072001 0.00263734766595279 -0.00335203317054354
0.000649182560833079 -0.0600811539449608 -0.0532302927543955
-0.0610788972957996 0.879292222162986 -0.0671585491960545
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0.00302588320632518,
-0.00307760776478522 -0.00440057005571037 0.000315784946773894
0.00127619111302658 -0.0038796568611528 0.00363727880259079
-0.00374826495168063 -0.0671585491960545 0.192814120948293
-0.00945658351920164 -0.00606262133808362 0.0046914027089562
-0.004438884246623 -0.0671585491960545 -0.00115357469371654
-0.00812915005220371 -0.00087088242454232 0.00278677511153939
-0.00127857569703387,
-0.00570142227559169 0.00130152304853031 0.000907927201776815
-0.00468114540689985 -0.00317015079634598 0.00403818130411868
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0.19293648386297 -0.00697067224578166 0.00544241984620045
-0.00495902048766524 -0.0663632831540068 -0.000807750615685828
-0.00937786434985094 -0.00134000398654133 -0.00104252061913907
0.00131431381988893,
-0.00611284035501395 -0.00127260662386009 -0.00131435643870052
0.000997520645385026 -0.00108032223173412 0.00614058033281912
-0.00145076821573348 -0.0631804285920365 -0.00606262133808362
-0.00697067224578166 0.162996130993493 0.00719901808495707
-0.00292685144986197 -0.0631804285920366 0.00105827907065204
-0.00605427137511552 0.000999373343633356 0.000186428893916974
0.00063451714890348,
-0.0209229212015547 -0.00011528684291611 -0.000590273074347901
-0.0019928296860267 0.0113936332689033 0.0181055932574402 0.0108263485342684
-0.0521664626950418 0.0046914027089562 0.00544241984620045
0.00719901808495707 0.0234530300552286 0.00888321057426696
-0.0521664626950419 0.0132735888470266 0.00478639995524257
0.0129679503540653 -0.00241482201075779 0.000163736468384719,
-0.0106347675953972 0.000314668319013466 0.00357311675973109
0.00161500892161912 0.00247729560164183 0.00759246318330849
0.000239412168812623 -0.0635368104539107 -0.004438884246623
-0.00495902048766524 -0.00292685144986197 0.00888321057426696
0.143485683962649 -0.0635368104539108 0.00260233610357529
-0.0050905739347665 0.00540184995175053 0.00143688870211674
-0.000606778563122093,
0.0525931189072001 0.00263734766595279 -0.00335203317054354
0.000649182560833082 -0.0600811539449608 -0.0532302927543955
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-0.0635368104539108 0.879292222162987 -0.0586769037238873
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0.00302588320632518,
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-0.00264578880577995 0.00479301167527537 0.012027509206273
0.00481922695478737 -0.0586769037238872 -0.00115357469371654
-0.000807750615685828 0.00105827907065204 0.0132735888470266
0.00260233610357529 -0.0586769037238873 0.0982860349413661
-0.00128039865615439 0.0063811027178823 0.0013092810433933
-0.00250636341693975,
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0.00106718826229541 -0.00356587017480307 0.00372904066454776
-0.00381085668543456 -0.0659606730287553 -0.00812915005220371
-0.00937786434985094 -0.00605427137511552 0.00478639995524257
-0.0050905739347665 -0.0659606730287554 -0.00128039865615439
0.191641294669898 -0.00125390488412485 0.000836515448322577
0.000156243937419144,
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-0.059162806946147 -0.00087088242454232 -0.00134000398654133
0.000999373343633356 0.0129679503540653 0.00540184995175053
-0.0591628069461471 0.0063811027178823 -0.00125390488412485
0.0945703277688909 0.000719840674021227 -0.000226754921770752,
0.00927090256437917 -0.00906240060991746 0.000688897706166622
0.000510838716778689 -0.000472225416095427 0.000395857625121327
0.000574343023851935 -0.00306400387811108 0.00278677511153939
-0.00104252061913907 0.000186428893916974 -0.00241482201075779
0.00143688870211674 -0.00306400387811108 0.0013092810433933
0.000836515448322577 0.000719840674021227 0.0230396533896294
-0.0161438569971946,
-0.00358411899712196 0.00914757285926523 0.00197347468700018
0.00266534906695824 -0.000670698384850352 -0.00115783914329167
-0.00131240178043079 0.00302588320632518 -0.00127857569703387
0.00131431381988893 0.00063451714890348 0.000163736468384719
-0.000606778563122093 0.00302588320632518 -0.00250636341693975
0.000156243937419144 -0.000226754921770752 -0.0161438569971946
0.017559095893398],
[1] || Design Nom(
:Product Family,
{"E", "G", "Y", "Z"}
) || Design Nom(
:Carrier,
{"Am", "AM", "AT", "CT", "deut", "NA", "Or",
"Retail", "SP", "TIM", "TM", "TF", "VZN", "VDF"
}
) || Design Nom( :Name( "I/M" ), {"F", "I", "O"} )
) * 3.49923396646939
)
La première partie du formulaire est une matrice 19 sur 19, ma question est de savoir comment traiter la deuxième partie de vec quadratique ([matrice 19 sur 19],
[ 1] || Nom de conception(
:Famille de produits,
{"E", "G", "Y", "Z"}
) || Nom de conception(
:Transporteur,
{"Am", "AM", "AT", "CT", "deut", "NA", "Ou",
"Retail", "SP", "TIM", "TM", "TF", "VZN", "VDF"
}
) || Conception Nom( :Nom( "I/M" ), {"F", "I", "O"} )
)
la deuxième partie comporte trois sections, 4 dans les familles de produits, 14 dans Carrier, 3 dans I/M, le total est de 21 éléments, j'essaie de porter la formule vers un autre langage logiciel. J'ai besoin d'aide pour comprendre ce formulaire.
Salut @Inigo ,
On dirait que vous êtes sur la plateforme Fit Y by X. Si tel est le cas, vous devriez pouvoir accéder au bouton rouge, sélectionner Fit Special, puis choisir les boutons radio "No Transformation" pour Y et X (en supposant que les données n'ont pas besoin d'être transformées), puis choisir le polynôme degré et DÉCOCHEZ la case "Polynôme centré".
Le polynôme centré est là par défaut car il permet une meilleure estimation des coefficients de l'ajustement.
J'espère que cela t'aides!,
DS
Salut,
Si vous enregistrez la formule de prédiction dans le tableau de données, puis ouvrez la formule dans l'éditeur de formules, sélectionnez "Simpliy" dans le deuxième hotspot rouge (voir l'image ci-dessous).
